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Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and analysis of large-scale 2D/3D scientific data
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/database structures, data transformation, algorithms, and data output by using appropriate computer language/tools to provide technical solutions for highly complex application development tasks. Direct
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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, APIs, and SDKs by reading documentation • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. • Experience with common data
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Requisition Id 15448 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large
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Computing Security. The candidate is expected to do cutting-edge research in multiple of the following areas, therefore prior expertise in these topics are highly encouraged: Quantum Machine Learning (QML
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multiple faculty clients at a time, and these engagements might last from a few days to several months. Your role will require you to listen carefully and critically to understand the faculty member’s
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methodologies underlying spatial data, high-dimensional and big data (e.g., data from wearable devices, electronic health records), Bayesian statistics, and learning algorithms as novel data analytical tools in
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applications for a Research Associate / Postdoctoral Associate position, in the area of Quantum Computing Security. The candidate is expected to do cutting-edge research in multiple of the following areas
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collaboration with multiple tech companies to develop and demonstrate the next generation of free-space optical (FSO) communication systems for satellite communications. Information Satellite-based links